I want to hold your hand: how music people and data people came together to drive change at EMI

In Data & Analytics by Freya Smale

David Boyle, big data, efficiency, customer relationship

Mr David Boyle, SVP Customer Insight, EMI Group joined us today at Big Data World  to present on how to drive change, and how it was successful at EMI. He focused on enabling a productive relationship between creative minded and analytic focused staff, recognising and using the skill set of each member of each team and how a united team can improve the consumer relationship. 

Data and insight is used in several ways at EMI, from more targeted marketing, to musicians using the information in their creative process to name but a few. 

The digital age bought about a new world to the music industry. Challenges include: needing to work with brands, changing business models, artist/manager relations, launching a new artist and connecting them with audiences, commercial relations and setting the agenda and PR of this newsworthy industry. Data can help! Firstly, it helps people choose. It provides information to experts and to non-experts. Data also helps build more effective business relationships.

At EMI, their data model begins with insight taken from a wide range of data, be it industry based or consumer research. The rest of the model recognises the skills and expertise alongside the data: these people drive the insight agenda, and this agenda drives them. This model aims to develop a business culture of evidence based decisions and reasoned arguments. 

What were the principles of the changes to EMI’s data programme?

Relevant, cheap and quick insight for all colleagues. Results should be powerful, broad, global and repeatable. It should add to our shared language and also guide decision-making and reasoning. This worked as it combined listening to in-house expertise, about hypotheses not conclusions and it was intuitive for both EMI and its partners. Key skill learnt from this data evolution is Reduction. Reduction of business question and of the data itself, to focus the analysis. The challenge: people not technology! People are present throughout the data value chain.

The final lesson learnt during this project at EMI was proving before building. Test what works before spending a lot of money. Expand once you know what works. This way you will know what you need before you invest: low risk option. 

Takeaways: work with the business, make insight a part of day-to-day, insight capability and the need for gut instinct!

To find out more check out www.MusicDataScience.com- a collaboration between EMI and Data Science London.